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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Ensuring solution and operations excellence	12.5%	- Implementing monitoring, logging, and observability 1. Alerting, dashboarding, and root cause analysis 2. Cloud Monitoring, Logging, and Error Reporting - Planning for continuous improvement 1. Technology updates and architecture evolution 2. Feedback loops and optimization cycles - Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars
Topic 2: Designing and planning a cloud solution architecture	25%	- Evaluating and selecting Google Cloud services 1. Compute, storage, database, and networking service selection 2. Serverless and managed service adoption - Planning cloud migration and hybrid/multi-cloud environments 1. Migration planning and execution 2. Data transfer and synchronization 3. Interoperability and integration design - Designing cloud solution infrastructure aligned with business requirements 1. Cost optimization strategies 2. Compliance and regulatory requirements consideration 3. Scalability, high availability, and fault tolerance design
Topic 3: Managing and provisioning solution infrastructure	15%	- Provisioning and managing compute resources 1. Auto-scaling and resource management 2. VMs, GKE, App Engine, Cloud Run deployment and management - Managing storage and data services 1. Database deployment, replication, and backup 2. Cloud Storage, Filestore, Persistent Disk management - Configuring network topologies and connectivity 1. VPC design, peering, and hybrid connectivity 2. Load balancing and CDN configuration
Topic 4: Managing implementation	12.5%	- Using Google Cloud tools and APIs programmatically 1. Infrastructure as Code (Terraform, Deployment Manager) 2. Cloud SDK, Cloud Shell, and Cloud Code - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation - Testing and validating solutions 1. Disaster recovery and failover testing 2. Functional, performance, and security testing
Topic 5: Analyzing and optimizing technical and business processes	15%	- Streamlining operational workflows 1. Change management and incident response 2. Stakeholder communication and alignment - Improving reliability and performance 1. SLO, SLA, and error budgeting 2. Latency reduction and throughput optimization - Optimizing cost and resource efficiency 1. Resource right-sizing and usage monitoring 2. Committed use discounts and pricing models
Topic 6: Designing for security and compliance	17.5%	- Securing data and communications 1. Encryption at rest and in transit 2. Key management and secret security - Implementing identity and access management 1. Organizational policies and resource hierarchy 2. IAM roles, permissions, and service accounts - Enforcing compliance and governance 1. Security controls, auditing, and logging 2. VPC Service Controls and security perimeters

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q70-Q75):

NEW QUESTION # 70
Your web application must comply with the requirements of the European Union's General Data Protection Regulation (GDPR). You are responsible for the technical architecture of your web application. What should you do?

A. Enable the relevant GDPR compliance setting within the GCPConsole for each of the services in use within your application.
B. Ensure that your web application only uses native features and services of Google Cloud Platform, because Google already has various certifications and provides "pass-on" compliance when you use native features.
C. Define a design for the security of data in your web application that meets GDPR requirements.
D. Ensure that Cloud Security Scanner is part of your test planning strategy in order to pick up any compliance gaps.

Answer: C

Explanation:
Explanation/Reference: https://www.mobiloud.com/blog/gdpr-compliant-mobile-app/

NEW QUESTION # 71
You are creating a solution to remove backup files older than 90 days from your backup Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend. What should you do?

A. Schedule a cron script using gsutil ls -1 gs://backups/** to find and remove items older than 90 days and schedule it with cron.
B. Write a lifecycle management rule in XML and push it to the bucket with gsutil.
C. Write a lifecycle management rule in JSON and push it to the bucket with gsutil.
D. Schedule a cron script using gsutil is -lr gs://backups/** to find and remove items older than 90 days.

Answer: C

Explanation:
https://cloud.google.com/storage/docs/gsutil/commands/lifecycle

NEW QUESTION # 72
Case Study: 2 - TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries: About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day.
TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment

TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
- Decrease unplanned vehicle downtime to less than 1 week, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP better position new products and services.
- Have the ability to partner with different companies-especially with
seed and fertilizer suppliers in the fast-growing agricultural
business-to create compelling joint offerings for their customers
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry dat

A. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.
B. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?
C. Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.
D. Have the vehicle' computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.
E. Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.

Answer: A

Explanation:
Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per- operation costs. For example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides low latency access to data stored as Coldline Storage.
References: https://cloud.google.com/storage/docs/storage-classes

NEW QUESTION # 73
One of the developers on your team deployed their application in Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.

You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality.
Which two actions should you take? Choose 2 answers.

A. Copy the source after the package dependencies (Python and pip) are installed.
B. Remove dependencies from requirements.txt.
C. Remove Python after running pip.
D. Use a slimmed-down base image like Alpine linux.
E. Use larger machine types for your Google Container Engine node pools.

Answer: A,D

Explanation:
Explanation
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/

NEW QUESTION # 74
You want to allow your operations team to store logs from all the production projects in your Organization, without including logs from other projects. All of the production projects are contained in a folder. You want to ensure that all logs for existing and new production projects are captured automatically. What should you do?

A. Create an aggregated export on the Production folder. Set the log sink to be a Cloud Storage bucket in an operations project.
B. Create log exports in the production projects. Set the log sinks to be BigQuery datasets in the production projects, and grant IAM access to the operations team to run queries on the datasets.
C. Create an aggregated export on the Organization resource. Set the log sink to be a Cloud Storage bucket in an operations project.
D. Create log exports in the production projects. Set the log sinks to be a Cloud Storage bucket in an operations project.

Answer: A

Explanation:
https://cloud.google.com/logging/docs/export/aggregated_sinks
Aggregated sinks combine and route log entries from the Google Cloud resources contained by an organization or folder.

NEW QUESTION # 75
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